Quality Versus Quantity: The Potential Impact of Public Reporting of Hospital Safety for Complex Cancer Surgery

Comparison of Hospital Volume and Risk-Standardized Mortality Rate as a Proxy for Hospital Quality in Complex Oncologic Hepatopancreatobiliary Surgery

BACKGROUND

Centralization of hepatopancreatobiliary procedures to more experienced centers has been recommended but remains controversial. Hospital volume and risk-stratified mortality rates (RSMR) are metrics for interhospital comparison. We compared facility operative volume with facility RSMR as a proxy for hospital quality.

PATIENTS AND METHODS

Patients who underwent surgery for liver (LC), biliary tract (BTC), and pancreatic (PDAC) cancer were identified in the National Cancer Database (2004-2018). Hierarchical logistic regression was used to create facility-specific models for RSMR. Volume (high versus low) was determined by quintile. Performance (high versus low) was determined by RSMR tercile. Primary outcomes included median facility RSMR and RSMR distributions. Volume- and RSMR-based redistribution was simulated and compared for reductions in 90-day mortality.

RESULTS

A total of 106,217 patients treated at 1282 facilities were included; 17,695 had LC, 23,075 had BTC, and 65,447 had PDAC. High-volume centers (HVC) had lower RSMR compared with medium-volume centers and low-volume centers for LC, BTC, and PDAC (all p < 0.001). High-performance centers (HPC) had lower RSMR compared with medium-performance centers and low-performance centers for LC, BTC, and PDAC (all p < 0.001). Volume-based redistribution required 16.0 patients for LC, 11.2 for BTC, and 14.9 for PDAC reassigned to 15, 22, and 20 centers, respectively, per life saved within each US census region. RSMR-based redistribution required 4.7 patients for LC, 4.2 for BTC, and 4.9 for PDAC reassigned to 316, 403, and 418 centers, respectively, per life saved within each US census region.

CONCLUSIONS

HVC and HPC have the lowest overall and risk-standardized 90-day mortality after oncologic hepatopancreatobiliary procedures, but RSMR may outperform volume as a measure of hospital quality.

Evaluation of ACS-NSQIP and CR-POSSUM risk calculators for the prediction of mortality after colorectal surgery: A retrospective cohort study

BACKGROUND

Several risk calculating tools have been introduced into clinical practice to provide patients and clinicians with objective, individualised estimates of procedure-related unfavourable outcomes. The currently available risk calculators (RCs) have been developed by well-endowed health systems in Europe and the USA. Applicability of these RCs in low-middle income country (LMIC) settings with wide disparities in patient population, surgical practice and healthcare infrastructure has not been adequately examined.

PATIENTS AND METHODS

Through this single tertiary care, LMIC-centre, retrospective cohort study, we investigated the accuracy of the two most widely validated RCs - American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) RC and ColoRectal Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (CR-POSSUM) - for the prediction of mortality in patients undergoing elective and emergency colorectal surgery (CRS) from March 2013 to March 2020. Online RCs were used to predict mortality and other outcomes. Accuracy was assessed by Brier score and C statistic.

RESULTS

Of 105 patients, 69 (65.71%) underwent elective and 36 (34.28%) underwent emergency CRS. The 30-day overall mortality was 12 - elective 1 (1.4%) and emergency 11 (30.5%). ACS-NSQIP RC performed better for the prediction of overall ( C statistic 0.939, Brier score 0.065) and emergency ( C statistic 0.840, Brier score 0.152) mortality. However, for elective CRS mortality, Brier scores were similar for both models (0.014), whereas C statistic (0.934 vs. 0.890) value was better for ACS-NSQIP.

CONCLUSIONS

Both ACS-NSQIP and CR-POSSUM were accurate for the prediction of CRS mortality. However, compared to CR-POSSUM, ACS-NSQIP performed better. The overall performance of both models is indicative of their wider applicability in LMIC centres also.

Comparison of Simulated Outcomes of Colorectal Cancer Surgery at the Highest-Performing vs Chosen Local Hospitals

IMPORTANCE

Variation in outcomes across hospitals adversely affects surgical patients. The use of high-quality hospitals varies by population, which may contribute to surgical disparities.

OBJECTIVE

To simulate the implications of data-driven hospital selection for social welfare among patients who underwent colorectal cancer surgery.

DESIGN, SETTING, AND PARTICIPANTS

This economic evaluation used the hospital inpatient file from the Florida Agency for Health Care Administration. Surgical outcomes of patients who were treated between January 1, 2016, and December 31, 2018 (training cohort), were used to estimate hospital performance. Costs and benefits of care at alternative hospitals were assessed in patients who were treated between January 1, 2019, and December 31, 2019 (testing cohort). The cohorts comprised patients 18 years or older who underwent elective colorectal resection for benign or malignant neoplasms. Data were analyzed from March to October 2022.

EXPOSURES

Using hierarchical logistic regression, we estimated the implications of hospital selection for in-hospital mortality risk in patients in the training cohort. These estimates were applied to patients in the testing cohort using bayesian simulations to compare outcomes at each patient's highest-performing and chosen local hospitals. Analyses were stratified by race and ethnicity to evaluate the potential implications for equity.

MAIN OUTCOMES AND MEASURES

The primary outcome was the mean patient-level change in social welfare, a composite measure balancing the value of reduced mortality with associated costs of care at higher-performing hospitals.

RESULTS

A total of 21 098 patients (mean [SD] age, 67.3 [12.0] years; 10 782 males [51.1%]; 2232 Black [10.6%] and 18 866 White [89.4%] individuals) who were treated at 178 hospitals were included. A higher-quality local hospital was identified for 3057 of 5000 patients (61.1%) in the testing cohort. Selecting the highest-performing hospital was associated with a 26.5% (95% CI, 24.5%-29.0%) relative reduction and 0.24% (95% CI, 0.23%-0.25%) absolute reduction in mortality risk. A mean amount of $1953 (95% CI, $1744-$2162) was gained in social welfare per patient treated. Simulated reassignment to a higher-quality local hospital was associated with a 23.5% (95% CI, 19.3%-32.9%) relative reduction and 0.26% (95% CI, 0.21%-0.30%) absolute reduction in mortality risk for Black patients, with $2427 (95% CI, $1697-$3158) gained in social welfare.

CONCLUSIONS AND RELEVANCE

In this economic evaluation, using procedure-specific hospital performance as the primary factor in the selection of a local hospital for colorectal cancer surgery was associated with improved outcomes for both patients and society. Surgical outcomes data can be used to transform care and guide policy in colorectal cancer.

Incidence of Liver Resection Following the Introduction of Caseload Requirements for Liver Surgery in Switzerland

Background

Centralization of care is an established concept in complex visceral surgery. Switzerland introduced case load requirements (CR) in 2013 in five areas of cancer surgery. The current study investigates the effects of CR on indication and mortality in liver surgery.

Methods

This is a retrospective analysis of a complete national in-hospital data set including all admissions between January 1, 2005, and December 31, 2015. Primary outcome variables were the incidence proportion and the 60-day in-hospital mortality of liver resections. Incidence proportion was calculated as the overall yearly number of liver resections performed in relation to the population living in Switzerland before and after the introduction of CR.

Results

Our analysis shows an increase number of liver resections compared to the period before introduction of CR from 2005–2012 (4.67 resections/100,000) to 2013–2015 (5.32 resections/100,000) after CR introduction. Age-adjusted incidence proportion increased by 14% (OR 1.14 95 CI [1.07–1.22]). National in-hospital mortality remained stable before and after CR (4.1 vs 3.7%), but increased in high-volume institutions (3.6 vs 5.6%). The number of hospitals performing liver resections decreased after the introduction of CR from 86 to 43. Half of the resections were performed in institutions reaching the stipulated numbers (53% before vs 49% after introduction of CR). After implementation of CR, patients undergoing liver surgery had more comorbidities (88 vs 92%).

Conclusion

The introduction of CR for liver surgery in Switzerland in 2013 was accompanied by an increase in operative volume with limited effects on centralization of care.

Risk-Adjusted Mortality Rates as a Quality Proxy Outperform Volume in Surgical Oncology-A New Perspective on Hospital Centralization Using National Population-Based Data

PURPOSE

Despite a long-known association between annual hospital volume and outcome, little progress has been made in shifting high-risk surgery to safer hospitals. This study investigates whether the risk-standardized mortality rate (RSMR) could serve as a stronger proxy for surgical quality than volume.

METHODS

We included all patients who underwent complex oncologic surgeries in Germany between 2010 and 2018 for any of five major cancer types, splitting the data into training (2010-2015) and validation sets (2016-2018). For each surgical group, we calculated annual volume and RSMR quintiles in the training set and applied these thresholds to the validation set. We studied the overlap between the two systems, modeled a market exit of low-performing hospitals, and compared effectiveness and efficiency of volume- and RSMR-based rankings. We compared travel distance or time that would be required to reallocate patients to the nearest hospital with low-mortality ranking for the specific procedure.

RESULTS

Between 2016 and 2018, 158,079 patients were treated in 974 hospitals. At least 50% of high-volume hospitals were not ranked in the low-mortality group according to RSMR grouping. In an RSMR centralization model, an average of 32 patients undergoing complex oncologic surgery would need to relocate to a low-mortality hospital to save one life, whereas 47 would need to relocate to a high-volume hospital. Mean difference in travel times between the nearest hospital to the hospital that performed surgery ranged from 10 minutes for colorectal cancer to 24 minutes for pancreatic cancer. Centralization on the basis of RSMR compared with volume would ensure lower median travel times for all cancer types, and these times would be lower than those observed.

CONCLUSION

RSMR is a promising proxy for measuring surgical quality. It outperforms volume in effectiveness, efficiency, and hospital availability for patients.

Medicare Advantage Networks and Access to High-volume Cancer Surgery Hospitals

OBJECTIVE

To determine how Medicare Advantage (MA) health plan networks impact access to high-volume hospitals for cancer surgery.

BACKGROUND

Cancer surgery at high-volume hospitals is associated with better short- and long-term outcomes. In the United States, health insurance is a major detriment to seeking care at high-volume hospitals. A third of older (>65 years) Americans are enrolled in privatized MA health plans. The impact of MA plan networks on access to high-volume surgery hospitals is unknown.

METHODS

We analyzed in-network hospitals for MA plans offered in Los Angeles county during open enrollment of 2015. For the purposes of this analysis, MA network data from provider directories were linked to hospital volume data from California Office of Statewide Health Planning and Development. Volume thresholds were based on published literature.

RESULTS

A total of 34 MA plans enrolled 554,754 beneficiaries in Los Angeles county during 2014 open enrollment for coverage starting in 2015 (MA penetration ∼43%). The proportion of MA plans that included high-volume cancer surgery hospital varied by the type of cancer surgery. While most plans (>71%) included at least one high-volume hospital for colon, rectum, lung, and stomach; 59% to 82% of MA plans did not include any high-volume hospitals for liver, esophagus, or pancreatic surgery. A significant proportion of beneficiaries in MA plans did not have access to high-volume hospitals for esophagus (93%), stomach (44%), liver (39%), or pancreas (70%) surgery. In contrast, nearly all MA beneficiaries had access to at least one high-volume hospital for lung (93%), colon (100%), or rectal (100%) surgery. Overall, Centers for Medicare & Medicaid Services plan rating or plan popularity were not correlated with access to high-volume hospital (P > 0.05).

CONCLUSIONS

The study identifies lack of high-volume hospital coverage in MA health plans as a major detriment in regionalization of cancer surgery impacting at least a third of older Americans.

Chemoradiation as a nonsurgical treatment option for early-stage esophageal cancers: a retrospective cohort study

Background

Complete tumor removal via esophagectomy or endoscopic excision has been associated with the greatest survival in early-stage esophageal cancer. However, patient health, anatomy, or goals of care may render patients ineligible for excision or resection. In this setting, chemoradiation (CRT) may be considered as a nonsurgical approach, however the outcomes associated with CRT in early-stage esophageal cancer are incompletely understood.

Methods

The National Cancer Database was queried for treatment-naïve cT1/T2, N0, M0 esophageal cancer patients managed with concurrent multi-agent CRT (≥50 Gy) between 2004 and 2015. Medically inoperable patients were excluded. Kaplan-Meier curves were generated to estimate 5-year overall survival (OS) from diagnosis in both stages.

Results

Of the 828 patients identified, 279 were cT1 and 549 were cT2. For cases after 2010, cT1 (N=124) was further stratified in cT1a (N=32, 25.8%) and cT1b (N=46, 37.1%). Kaplan-Meier estimates demonstrated a 5-year survival of 21.7% for cT1 and 25.9% for cT2. Sensitivity analyses were performed to mitigate competing survival risk from poor health. Among 589 comorbidity-free patients (i.e., Charlson = score zero), the 5-year survival with CRT was 23.4% for cT1 and 27.8% for cT2. Finally, a subset of patients who refused a recommended surgery were evaluated with 5-year survival cT1 =33.5% and cT2 =33.4%).

Conclusions

Up to a third of selected patients with early-stage esophageal cancer may be cured after CRT as definitive non-surgical treatment. However, cure rates may be underestimated in this setting, secondary to persistent health-related bias.

Physicochemical parameters that underlie inkjet printing for medical applications

One of the most common types of 3D printing technologies is inkjet printing due to its numerous advantages, including low cost, programmability, high resolution, throughput, and speed. Inkjet printers are also capable of fabricating artificial tissues with physiological characteristics similar to those of living tissues. These artificial tissues are used for disease modeling, drug discovery, drug screening, and replacements for diseased or damaged tissues. This paper reviews recent advancements in one of the most common 3D printing technologies, inkjet dispensing. We briefly consider common printing techniques, including fused deposition modeling (FDM), stereolithography (STL), and inkjet printing. We briefly discuss various steps in inkjet printing, including droplet generation, droplet ejection, interaction of droplets on substrates, drying, and solidification. We also discuss various parameters that affect the printing process, including ink properties (e.g., viscosity and surface tension), physical parameters (e.g., internal diameter of printheads), and actuation mechanisms (e.g., piezoelectric actuation and thermal actuation). Through better understanding of common 3D printing technologies and the parameters that influence the printing processes, new types of artificial tissues, disease models, and structures for drug discovery and drug screening may be prepared. This review considers future directions in inkjet printing research that are focused on enhancing the resolution, printability, and uniformity of printed structures.

Navigating by Stars: Using CMS Star Ratings to Choose Hospitals for Complex Cancer Surgery

Background

The Centers for Medicare and Medicaid Services (CMS) developed risk-adjusted “Star Ratings,” which serve as a guide for patients to compare hospital quality (1 star = lowest, 5 stars = highest). Although star ratings are not based on surgical care, for many procedures, surgical outcomes are concordant with star ratings. In an effort to address variability in hospital mortality after complex cancer surgery, the use of CMS Star Ratings to identify the safest hospitals was evaluated.

Methods

Patients older than 65 years of age who underwent complex cancer surgery (lobectomy, colectomy, gastrectomy, esophagectomy, pancreaticoduodenectomy) were evaluated in CMS Medicare Provider Analysis and Review files (2013-2016). The impact of reassignment was modeled by applying adjusted mortality rates of patients treated at 5-star hospitals to those at 1-star hospitals (Peters-Belson method).

Results

There were 105 823 patients who underwent surgery at 3146 hospitals. The 90-day mortality decreased with increasing star rating (1 star = 10.4%, 95% confidence interval [CI] = 9.8% to 11.1%; and 5 stars = 6.4%, 95% CI = 6.0% to 6.8%). Reassignment of patients from 1-star to 5-star hospitals (7.8% of patients) was predicted to save 84 Medicare beneficiaries each year. This impact varied by procedure (colectomy = 47 lives per year; gastrectomy = 5 lives per year). Overall, 2189 patients would have to change hospitals each year to improve outcomes (26 patients moved to save 1 life).

Conclusions

Mortality after complex cancer surgery is associated with CMS Star Rating. However, the use of CMS Star Ratings by patients to identify the safest hospitals for cancer surgery would be relatively inefficient and of only modest impact.

Survival After Cancer Treatment at Top-Ranked US Cancer Hospitals vs Affiliates of Top-Ranked Cancer Hospitals

IMPORTANCE

Hospital networks formed around top-ranked cancer hospitals represent an opportunity to optimize complex cancer care in the community.

OBJECTIVE

To compare the short- and long-term survival after complex cancer treatment at top-ranked cancer hospitals and the affiliates of top-ranked hospitals.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted using data from the unabridged version of the National Cancer Database. Included patients were individuals 18 years or older who underwent surgical treatment for esophageal, gastric, lung, pancreatic, colorectal, or bladder cancer diagnosed between January 1, 2012, and December 31, 2016. Patient outcomes after complex surgical procedures for cancer at top-ranked cancer hospitals (as ranked in top 50 by US News and World Report) were compared with outcomes at affiliates of top-ranked cancer hospitals (affiliation listed in American Hospitals Association survey and confirmed by search of internet presence). Data were analyzed from July through December 2019.

EXPOSURES

Undergoing complex cancer treatment at a top-ranked cancer hospital or an affiliated hospital.

MAIN OUTCOMES AND MEASURES

The association of affiliate status with short-term survival (ie, 90-day mortality) was compared using logistic regression, and the association of affiliate status with long-term survival was compared using time-to-event models, adjusting for patient demographic, payer, clinical, and treatment factors.

RESULTS

Among 119 834 patients who underwent surgical treatment for cancer, 79 981 patients (66.7%) were treated at top-ranked cancer hospitals (median [interquartile range] age, 66 [58-74] years; 40 910 [54.9%] men) and 39 853 patients (33.3%) were treated at affiliate hospitals (median [interquartile range] age, 69 [60-77] years; 19 004 [50.0%] men). In a pooled analysis of all cancer types, adjusted perioperative mortality within 90 days of surgical treatment was higher at affiliate hospitals compared with top-ranked hospitals (odds ratio, 1.67 [95% CI, 1.49-1.89]; P < .001). Adjusted long-term survival following cancer treatment at affiliate hospitals was only 77% that of top-ranked hospitals (time ratio, 0.77 [95% CI, 0.72-0.83]; P < .001). The survival advantage was not fully explained by differences in annual surgical volume, with both long- and short-term survival remaining superior at top-ranked hospitals even after models were adjusted for volume.

CONCLUSIONS AND RELEVANCE

These findings suggest that short- and long-term survival after complex cancer treatment were superior at top-ranked hospitals compared with affiliates of top-ranked hospitals. Further study of cancer care within top-ranked cancer networks could reveal collaborative opportunities to improve survival across a broad contingent of the US population.

Assessment of variation in 30-day mortality following cancer surgeries among older adults across US hospitals

Background

While public reporting of surgical outcomes for noncancer conditions is common, cancer surgeries have generally been excluded. This is true despite numerous studies showing outcomes to differ between hospitals based on their characteristics. Our objective was to assess whether three prerequisites for quality assessment and reporting are present for 30‐day mortality after cancer surgery: low burden for timely reporting, hospital variation, and potential for public health gains.

Study Design

We used Fee‐for‐Service (FFS) Medicare claims to examine the extent of variation in 30‐day cancer surgical mortality between 3860 US hospitals. We included 340 489 surgeries for 12 cancer types for FFS Medicare beneficiaries aged ≥66 years, 2011‐2013. Hierarchical mixed‐effects logistic regression models adjusted for patient and hospital characteristics and with a random hospital effect were fit to obtain hospital‐specific risk‐standardized mortality rates (RSMRs) and 99% confidence intervals (CI). We calculated a hospital odds ratio to describe the difference in mortality risk for a hospital above vs below average quality and estimated the potential mortality reduction.

Results

The median number of cancer surgeries per hospital was 34. The median RSMR overall was 2.41% (99% CI 2.28%, 2.66%). In aggregate and for most cancers, variation between hospitals exceeded that due to differences in patient and hospital characteristics. For individual cancers, relative differences exceeded 20% in mortality risk between patients undergoing surgery at a hospital below vs above average quality, with the potential for an estimated 500 deaths prevented annually given hypothetical improvements.

Conclusion

Quality measurement and reporting of 30‐day mortality for cancer surgery is worthy of consideration.

Regionalization of esophagectomy: where are we now?

The morbidity and mortality benefits of performing high-risk operations in high-volume centers by high-volume surgeons are evident. Regionalization is a proposed strategy to leverage high-volume centers for esophagectomy to improve quality outcomes. Internationally, regionalization occurs under national mandates. Those mandates do not exist in the United States and spontaneous regionalization of esophagectomy has only modestly occurred in the U.S. Regionalization must strike a careful balance and not limit access to optimal oncologic care to our most vulnerable cancer patient populations in rural and disadvantaged socioeconomic areas. We reviewed the recent literature highlighting: the justification of hospital and surgeon annual esophagectomy volumes for regionalization; how safety performance metrics could influence regionalization; whether regionalization is occurring in the US; what impact regionalization may have on esophagectomy costs; and barriers to patients traveling to receive oncologic treatment at regionalized centers of excellence.

Differential Safety Between Top-Ranked Cancer Hospitals and Their Affiliates for Complex Cancer Surgery

IMPORTANCE

Leading cancer hospitals have increasingly shared their brands with other hospitals through growing networks of affiliations. However, the brand of top-ranked cancer hospitals may evoke distinct reputations for safety and quality that do not extend to all hospitals within these networks.

OBJECTIVE

To assess perioperative mortality of Medicare beneficiaries after complex cancer surgery across hospitals participating in networks with top-ranked cancer hospitals.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional study was performed of the Centers for Medicare & Medicaid Services 100% Medicare Provider and Analysis Review file from January 1, 2013, to December 31, 2016, for top-ranked cancer hospitals (as assessed by U.S. News and World Report) and affiliated hospitals that share their brand. Participants were 29 228 Medicare beneficiaries older than 65 years who underwent complex cancer surgery (lobectomy, esophagectomy, gastrectomy, colectomy, and pancreaticoduodenectomy [Whipple procedure]) between January 1, 2013, and October 1, 2016.

EXPOSURES

Undergoing complex cancer surgery at a top-ranked cancer hospital vs an affiliated hospital.

MAIN OUTCOMES AND MEASURES

Risk-adjusted 90-day mortality estimated using hierarchical logistic regression and comparison of the relative safety of hospitals within each cancer network estimated using standardized mortality ratios.

RESULTS

A total of 17 300 patients (59.2%; 8612 women and 8688 men; mean [SD] age, 74.7 [6.2] years) underwent complex cancer surgery at 59 top-ranked hospitals and 11 928 patients (40.8%; 6287 women and 5641 men; mean [SD] age, 76.2 [6.9] years) underwent complex cancer surgery at 343 affiliated hospitals. Overall, surgery performed at affiliated hospitals was associated with higher 90-day mortality (odds ratio, 1.40; 95% CI, 1.23-1.59; P < .001), with odds ratios that ranged from 1.32 (95% CI, 1.12-1.56; P = .001) for colectomy to 2.04 (95% CI, 1.41-2.95; P < .001) for gastrectomy. When the relative safety of each top-ranked cancer hospital was compared with its collective affiliates, the top-ranked hospital was safer than the affiliates in 41 of 49 studied networks (83.7%; 95% CI, 73.1%-93.3%).

CONCLUSIONS AND RELEVANCE

The likelihood of surviving complex cancer surgery appears to be greater at top-ranked cancer hospitals compared with the affiliated hospitals that share their brand. Further investigation of performance across trusted cancer networks could enhance informed decision making for complex cancer care.

Motivators, Barriers, and Facilitators to Traveling to the Safest Hospitals in the United States for Complex Cancer Surgery

IMPORTANCE

Directing patients to safer hospitals for complex cancer surgery (regionalization) may prevent thousands of mortalities in the United States.

OBJECTIVE

To understand the potential for individuals to move to safer hospitals: what would inspire them to travel (motivators), what challenges would they face (barriers), and what would enable them to travel (facilitators).

DESIGN, SETTING, AND PARTICIPANTS

This nationally representative online survey study asked respondents to consider complex cancer surgery at their local hospital or a hospital specializing in cancer an hour farther away. Completed surveys were weighted across sociodemographics to be nationally representative and outcomes were reported as weighted percentages. In January 2018, a panel of 1817 US adults recruited by address- and telephone-based sampling to be nationally representative were invited to take the survey. Data analysis was conducted from January 24, 2018, to September 19, 2018.

MAIN OUTCOMES AND MEASURES

Proportion of respondents motivated to travel by specific quality and safety indicators (motivators), magnitude in difference that would be necessary, proportion facing specific barriers, and proportion enabled to move by facilitators. Resistant individuals were identified as people who would not travel except for the largest (top quartile) outcomes differences.

RESULTS

There were 1016 completed surveys (response rate of 55.9%). The weighted median age was 48 years, 52% were female, median annual income was between $60 000 and $75 000, and 85% lived in a metropolitan area. Nonresponders were more likely than responders to be female, younger, nonwhite, less educated, and lower income (female: 54.4% vs 48.3%; P = .01; younger [aged <45 years]: 56.3% vs 37.1%; P < .001; nonwhite: 41.6% vs 30.0%; P < .001; less than college education: 43.8% vs 32.4%; P < .001; income <$30 000: 22.1% vs 17.1%; P = .01). Superior safety or oncologic outcomes, presented separately, motivated an average of 92% of respondents (95% CI, 90%-94%) to travel. One-third were easily motivated, requiring less than 1% advantage in safety or quality, while 12% were particularly resistant across outcomes. Respondents with lower income (income <$25 000: odds ratio, 2.01; 95% CI, 1.19-3.39) and nonwhite race (odds ratio, 1.60; 95% CI, 1.05-2.42) were more resistant to travel. At least 1 barrier was identified by 74% of respondents (95% CI, 72%-77%), most commonly financial (costs/insurance). However, 94% of respondents (95% CI, 92%-96%) with barriers would travel if provided facilitators, many of which were relatively low cost (transportation, parking, and hotel).

CONCLUSIONS AND RELEVANCE

It appears that most of the US public could be motivated to travel to safer hospitals for complex cancer surgery, yet most would require some support to move. Further efforts to ensure that benefits from regionalization are equitable across sociodemographic strata are indicated.

Why Travel for Complex Cancer Surgery? Americans React to 'Brand-Sharing' Between Specialty Cancer Hospitals and Their Affiliates

INTRODUCTION

Leading cancer hospitals have increasingly shared their 'brand' with smaller hospitals through affiliations. Because each brand evokes a distinct reputation for the care provided, 'brand-sharing' has the potential to impact the public's ability to differentiate the safety and quality within hospital networks. The general public was surveyed to determine the perceived similarities and differences in the safety and quality of complex cancer surgery performed at top cancer hospitals and their smaller affiliate hospitals.

METHODS

A national, web-based KnowledgePanel (GfK) survey of American adults was conducted. Respondents were asked about their beliefs regarding the quality and safety of complex cancer surgery at a large, top-ranked cancer hospital and a smaller, local hospital, both in the presence and absence of an affiliation between the hospitals.

RESULTS

A total of 1010 surveys were completed (58.1% response rate). Overall, 85% of respondents felt 'motivated' to travel an hour for complex surgery at a larger hospital specializing in cancer, over a smaller local hospital. However, if the smaller hospital was affiliated with a top-ranked cancer hospital, 31% of the motivated respondents changed their preference to the smaller hospital. When asked to compare leading cancer hospitals and their smaller affiliates, 47% of respondents felt that surgical safety, 66% felt guideline compliance, and 53% felt cure rates would be the same at both hospitals.

CONCLUSIONS

Approximately half of surveyed Americans did not distinguish the quality and safety of surgical care at top-ranked cancer hospitals from their smaller affiliates, potentially decreasing their motivation to travel to top centers for complex surgical care.